AI Medical Compendium Journal:
Clinical implant dentistry and related research

Showing 1 to 8 of 8 articles

Automated Segmentation of Graft Material in 1-Stage Sinus Lift Based on Artificial Intelligence: A Retrospective Study.

Clinical implant dentistry and related research
OBJECTIVES: Accurate assessment of postoperative bone graft material changes after the 1-stage sinus lift is crucial for evaluating long-term implant survival. However, traditional manual labeling and segmentation of cone-beam computed tomography (CB...

A transcrestal sinus floor elevation strategy based on a haptic robot system: An in vitro study.

Clinical implant dentistry and related research
OBJECTIVES: To reveal the force profiles recorded by haptic autonomous robotic force feedback during the transcrestal sinus floor elevation (TSFE) process, providing a reference for the surgery strategy during TSFE.

Artificial intelligence and mixed reality for dental implant planning: A technical note.

Clinical implant dentistry and related research
AIM: The aim of this work is to present a new protocol for implant surgical planning which involves the combined use of artificial intelligence (AI) and mixed reality (MR).

Emergence of artificial intelligence for automating cone-beam computed tomography-derived maxillary sinus imaging tasks. A systematic review.

Clinical implant dentistry and related research
Cone-beam computed tomography (CBCT) imaging of the maxillary sinus is indispensable for implantologists, offering three-dimensional anatomical visualization, morphological variation detection, and abnormality identification, all critical for diagnos...

Deep learning in the overall process of implant prosthodontics: A state-of-the-art review.

Clinical implant dentistry and related research
Artificial intelligence represented by deep learning has attracted attention in the field of dental implant restoration. It is widely used in surgical image analysis, implant plan design, prosthesis shape design, and prognosis judgment. This article ...

Deep learning for the identification of ridge deficiency around dental implants.

Clinical implant dentistry and related research
OBJECTIVES: This study aimed to use a deep learning (DL) approach for the automatic identification of the ridge deficiency around dental implants based on an image slice from cone-beam computerized tomography (CBCT).

Accuracy of a Cascade Network for Semi-Supervised Maxillary Sinus Detection and Sinus Cyst Classification.

Clinical implant dentistry and related research
OBJECTIVE: Maxillary sinus mucosal cysts represent prevalent oral and maxillofacial diseases, and their precise diagnosis is essential for surgical planning in maxillary sinus floor elevation. This study aimed to develop a deep learning-based pipelin...

Artificial Intelligence-Based Detection and Numbering of Dental Implants on Panoramic Radiographs.

Clinical implant dentistry and related research
OBJECTIVES: This study aimed to develop an artificial intelligence (AI)-based deep learning model for the detection and numbering of dental implants in panoramic radiographs. The novelty of this model lies in its ability to both detect and number imp...